Literature DB >> 23138306

Protein structure prediction from sequence variation.

Debora S Marks1, Thomas A Hopf, Chris Sander.   

Abstract

Genomic sequences contain rich evolutionary information about functional constraints on macromolecules such as proteins. This information can be efficiently mined to detect evolutionary couplings between residues in proteins and address the long-standing challenge to compute protein three-dimensional structures from amino acid sequences. Substantial progress has recently been made on this problem owing to the explosive growth in available sequences and the application of global statistical methods. In addition to three-dimensional structure, the improved understanding of covariation may help identify functional residues involved in ligand binding, protein-complex formation and conformational changes. We expect computation of covariation patterns to complement experimental structural biology in elucidating the full spectrum of protein structures, their functional interactions and evolutionary dynamics.

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Year:  2012        PMID: 23138306      PMCID: PMC4319528          DOI: 10.1038/nbt.2419

Source DB:  PubMed          Journal:  Nat Biotechnol        ISSN: 1087-0156            Impact factor:   54.908


  52 in total

1.  Progress in predicting inter-residue contacts of proteins with neural networks and correlated mutations.

Authors:  P Fariselli; O Olmea; A Valencia; R Casadio
Journal:  Proteins       Date:  2001

2.  Some observations on the basic principles of design in protein molecules.

Authors:  C B ANFINSEN
Journal:  Comp Biochem Physiol       Date:  1962-10

3.  Scoring function for automated assessment of protein structure template quality.

Authors:  Yang Zhang; Jeffrey Skolnick
Journal:  Proteins       Date:  2004-12-01

4.  Genomics-aided structure prediction.

Authors:  Joanna I Sułkowska; Faruck Morcos; Martin Weigt; Terence Hwa; José N Onuchic
Journal:  Proc Natl Acad Sci U S A       Date:  2012-06-12       Impact factor: 11.205

5.  Coevolution of PDZ domain-ligand interactions analyzed by high-throughput phage display and deep sequencing.

Authors:  Andreas Ernst; David Gfeller; Zhengyan Kan; Somasekar Seshagiri; Philip M Kim; Gary D Bader; Sachdev S Sidhu
Journal:  Mol Biosyst       Date:  2010-08-11

6.  Toward high-resolution de novo structure prediction for small proteins.

Authors:  Philip Bradley; Kira M S Misura; David Baker
Journal:  Science       Date:  2005-09-16       Impact factor: 47.728

7.  Weak pairwise correlations imply strongly correlated network states in a neural population.

Authors:  Elad Schneidman; Michael J Berry; Ronen Segev; William Bialek
Journal:  Nature       Date:  2006-04-09       Impact factor: 49.962

8.  Assessment of domain boundary predictions and the prediction of intramolecular contacts in CASP8.

Authors:  Iakes Ezkurdia; Osvaldo Graña; José M G Izarzugaza; Michael L Tress
Journal:  Proteins       Date:  2009

9.  CASP9 results compared to those of previous CASP experiments.

Authors:  Andriy Kryshtafovych; Krzysztof Fidelis; John Moult
Journal:  Proteins       Date:  2011-10-14

10.  ModBase, a database of annotated comparative protein structure models, and associated resources.

Authors:  Ursula Pieper; Benjamin M Webb; David T Barkan; Dina Schneidman-Duhovny; Avner Schlessinger; Hannes Braberg; Zheng Yang; Elaine C Meng; Eric F Pettersen; Conrad C Huang; Ruchira S Datta; Parthasarathy Sampathkumar; Mallur S Madhusudhan; Kimmen Sjölander; Thomas E Ferrin; Stephen K Burley; Andrej Sali
Journal:  Nucleic Acids Res       Date:  2010-11-19       Impact factor: 16.971

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  235 in total

1.  Constructing sequence-dependent protein models using coevolutionary information.

Authors:  Ryan R Cheng; Mohit Raghunathan; Jeffrey K Noel; José N Onuchic
Journal:  Protein Sci       Date:  2015-08-10       Impact factor: 6.725

2.  The functional role of the αM4 transmembrane helix in the muscle nicotinic acetylcholine receptor probed through mutagenesis and coevolutionary analyses.

Authors:  Mackenzie J Thompson; Jaimee A Domville; John E Baenziger
Journal:  J Biol Chem       Date:  2020-06-11       Impact factor: 5.157

3.  Synthetic protein alignments by CCMgen quantify noise in residue-residue contact prediction.

Authors:  Susann Vorberg; Stefan Seemayer; Johannes Söding
Journal:  PLoS Comput Biol       Date:  2018-11-05       Impact factor: 4.475

4.  Predicting functionally informative mutations in Escherichia coli BamA using evolutionary covariance analysis.

Authors:  Robert S Dwyer; Dante P Ricci; Lucy J Colwell; Thomas J Silhavy; Ned S Wingreen
Journal:  Genetics       Date:  2013-08-09       Impact factor: 4.562

Review 5.  The functional importance of co-evolving residues in proteins.

Authors:  Inga Sandler; Nitzan Zigdon; Efrat Levy; Amir Aharoni
Journal:  Cell Mol Life Sci       Date:  2013-09-01       Impact factor: 9.261

6.  BCov: a method for predicting β-sheet topology using sparse inverse covariance estimation and integer programming.

Authors:  Castrense Savojardo; Piero Fariselli; Pier Luigi Martelli; Rita Casadio
Journal:  Bioinformatics       Date:  2013-09-23       Impact factor: 6.937

Review 7.  Reads meet rotamers: structural biology in the age of deep sequencing.

Authors:  Anurag Sethi; Declan Clarke; Jieming Chen; Sushant Kumar; Timur R Galeev; Lynne Regan; Mark Gerstein
Journal:  Curr Opin Struct Biol       Date:  2015-12-01       Impact factor: 6.809

8.  Determining protein structures by combining semireliable data with atomistic physical models by Bayesian inference.

Authors:  Justin L MacCallum; Alberto Perez; Ken A Dill
Journal:  Proc Natl Acad Sci U S A       Date:  2015-05-18       Impact factor: 11.205

Review 9.  Structure-Encoded Global Motions and Their Role in Mediating Protein-Substrate Interactions.

Authors:  Ivet Bahar; Mary Hongying Cheng; Ji Young Lee; Cihan Kaya; She Zhang
Journal:  Biophys J       Date:  2015-07-02       Impact factor: 4.033

10.  Distance-based protein folding powered by deep learning.

Authors:  Jinbo Xu
Journal:  Proc Natl Acad Sci U S A       Date:  2019-08-09       Impact factor: 11.205

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